Search results for: supervised multiclass classification

Authors: Elmi Abu Bakar, Tetsuo Miyake, Zhong Zhang, Takashi Imamura

Abstract:

Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.

Keywords: CAD, rendering, feature extraction, feature classification.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1976

Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

Abstract:

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: Data mining, knowledge discovery in databases, prediction models, student success.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2538

Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1935

Authors: M. Rahmati, S.M. Mirzababaei

Abstract:

With the advance of information technology in the new era the applications of Internet to access data resources has steadily increased and huge amount of data have become accessible in various forms. Obviously, the network providers and agencies, look after to prevent electronic attacks that may be harmful or may be related to terrorist applications. Thus, these have facilitated the authorities to under take a variety of methods to protect the special regions from harmful data. One of the most important approaches is to use firewall in the network facilities. The main objectives of firewalls are to stop the transfer of suspicious packets in several ways. However because of its blind packet stopping, high process power requirements and expensive prices some of the providers are reluctant to use the firewall. In this paper we proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. By discriminating these data, an administrator may take an approach action against the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1654

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: Image fusion, iris recognition, local binary pattern, wavelet.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2215

Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: Centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1686

Authors: Zhongjie Wang, Xiaofei Xu, Dechen Zhan

Abstract:

With deep development of software reuse, componentrelated technologies have been widely applied in the development of large-scale complex applications. Component identification (CI) is one of the primary research problems in software reuse, by analyzing domain business models to get a set of business components with high reuse value and good reuse performance to support effective reuse. Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification process. Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods, with the comparisons between these methods for their advantages and disadvantages. Additionally, some insufficiencies of study on CI are discussed, and the causes are explained subsequently. Finally, it is concluded with some significantly promising tendency about research on this problem.

Keywords: Business component, component granularity, component identification, reuse performance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1973

Authors: Monika Chuchro

Abstract:

This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain subgroups of time series data with normal distribution from the inflow into wastewater treatment plant data, composed of several groups differing by mean value. Two simple algorithms, K-mean and EM, were chosen as a clustering method. The Rand index was used to measure the similarity. After simple meta-clustering, a regression model was performed for each subgroups. The final model was a sum of the subgroups models. The quality of the obtained model was compared with the regression model made using the same explanatory variables, but with no clustering of data. Results were compared using determination coefficient (R2), measure of prediction accuracy- mean absolute percentage error (MAPE) and comparison on a linear chart. Preliminary results allow us to foresee the potential of the presented technique.

Keywords: Clustering, Data analysis, Data mining, Predictive models.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1950

Authors: Siyao Zhu, Yifang Xu

Abstract:

After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. Brain-computer interface is a promising option to overcome the limitations of tedious manual control and operation of robots in the urgent search-and-rescue tasks. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: Consensus assessment, electroencephalogram, EEG, emergency response, human-robot collaboration, intention recognition, search and rescue.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 343

Authors: J. Bouchard, B. Prosperi, G. Bavre, M. Daudé, E. Jeandupeux

Abstract:

Young patients suffering from Cerebral Palsy are facing difficult choices concerning heavy surgeries. Diagnosis settled by surgeons can be complex and on the other hand decision for patient about getting or not such a surgery involves important reflection effort. Proposed software combining prediction for surgeries and post surgery kinematic values, and from 3D model representing the patient is an innovative tool helpful for both patients and medicine professionals. Beginning with analysis and classification of kinematics values from Data Base extracted from gait analysis in 3 separated clusters, it is possible to determine close similarity between patients. Prediction surgery best adapted to improve a patient gait is then determined by operating a suitable preconditioned neural network. Finally, patient 3D modeling based on kinematic values analysis, is animated thanks to post surgery kinematic vectors characterizing the closest patient selected from patients clustering.

Keywords: Cerebral Palsy, Clustering, Crouch Gait, 3-D Modeling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2006

Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

Abstract:

Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3138

Authors: Huanjun Liu, Yaonan Wang, Feng Duan

Abstract:

This text studies glass bottle intelligent inspector based machine vision instead of manual inspection. The system structure is illustrated in detail in this paper. The text presents the method based on watershed transform methods to segment the possible defective regions and extract features of bottle wall by rules. Then wavelet transform are used to exact features of bottle finish from images. After extracting features, the fuzzy support vector machine ensemble is putted forward as classifier. For ensuring that the fuzzy support vector machines have good classification ability, the GA based ensemble method is used to combining the several fuzzy support vector machines. The experiments demonstrate that using this inspector to inspect glass bottles, the accuracy rate may reach above 97.5%.

Keywords: Intelligent Inspection, Support Vector Machines, Ensemble Methods, watershed transform, Wavelet Transform

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3894

Authors: Gemma García López

Abstract:

The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: Emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 713

Authors: Omer Rashid, Ayoub Al-Hamadi, Axel Panning, Bernd Michaelis

Abstract:

It is hard to percept the interaction process with machines when visual information is not available. In this paper, we have addressed this issue to provide interaction through visual techniques. Posture recognition is done for American Sign Language to recognize static alphabets and numbers. 3D information is exploited to obtain segmentation of hands and face using normal Gaussian distribution and depth information. Features for posture recognition are computed using statistical and geometrical properties which are translation, rotation and scale invariant. Hu-Moment as statistical features and; circularity and rectangularity as geometrical features are incorporated to build the feature vectors. These feature vectors are used to train SVM for classification that recognizes static alphabets and numbers. For the alphabets, curvature analysis is carried out to reduce the misclassifications. The experimental results show that proposed system recognizes posture symbols by achieving recognition rate of 98.65% and 98.6% for ASL alphabets and numbers respectively.

Keywords: Feature Extraction, Posture Recognition, Pattern Recognition, Application.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1518

Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: Hybrid systems, Hidden Markov Models, Recurrent neural networks, Deterministic finite state automata.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2883

Authors: Xiaohua Liu, Juan F. Beltran, Nishant Mohanchandra, Godfried T. Toussaint

Abstract:

Support vector machines (SVMs) are considered to be the best machine learning algorithms for minimizing the predictive probability of misclassification. However, their drawback is that for large data sets the computation of the optimal decision boundary is a time consuming function of the size of the training set. Hence several methods have been proposed to speed up the SVM algorithm. Here three methods used to speed up the computation of the SVM classifiers are compared experimentally using a musical genre classification problem. The simplest method pre-selects a random sample of the data before the application of the SVM algorithm. Two additional methods use proximity graphs to pre-select data that are near the decision boundary. One uses k-Nearest Neighbor graphs and the other Relative Neighborhood Graphs to accomplish the task.

Keywords: Machine learning, data mining, support vector machines, proximity graphs, relative-neighborhood graphs, k-nearestneighbor graphs, random sampling, training data condensation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1918

Authors: Maziyar Nouraee

Abstract:

Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: Electronic Commerce, Electronic Market, B2B Trade, Supply Chain Management.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2008

Authors: Wenji Zhu, Yigang He

Abstract:

This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.

Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2198

Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: Feature fusion, image retrieval, membership function, normalization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1342

Authors: Asar Khan, Peter D. Widdop, Andrew J. Day, Aliaster S. Wood, Steve, R. Mounce, John Machell

Abstract:

This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by sensors to construct an empirical model for time series prediction and classification of events. These two components have been installed, tested and verified in an experimental site in a UK water distribution system. Verification of the system has been achieved from a series of simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network management.

Keywords: Detection, leakage, neural networks, sensors, water distribution networks

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1744

Authors: K. Badron, A. F. Ismail, A. L. Asnawi, N. F. A. Malik, S. Z. Abidin, S. Dzulkifly

Abstract:

The occurrences of precipitation, also commonly referred as rain, in the form of "convective" and "stratiform" have been identified to exist worldwide. In this study, the radar return echoes or known as reflectivity values acquired from radar scans have been exploited in the process of classifying the type of rain endured. The investigation use radar data from Malaysian Meteorology Department (MMD). It is possible to discriminate the types of rain experienced in tropical region by observing the vertical characteristics of the rain structure. .Heavy rain in tropical region profoundly affects radiowave signals, causing transmission interference and signal fading. Required wireless system fade margin depends on the type of rain. Information relating to the two mentioned types of rain is critical for the system engineers and researchers in their endeavour to improve the reliability of communication links. This paper highlights the quantification of percentage occurrences over one year period in 2009.

Keywords: Stratiform, convective, tropical region, attenuation radar reflectivity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1443

Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 258

Authors: Dubbale Daniel A., Tsutsumi J.

Abstract:

This research work takes a different approach in the discussion of urban form impacts on transport planning and auto dependency. Concentrated density represented by effective density explains auto dependency better than the conventional density and it is proved to be a realistic density representative for the urban transportation analysis. Model analysis reveals that effective density is influenced by the shopping accessibility index as well as job density factor. It is also combined with the job access variable to classify four levels of Transport Activity Centers (TACs) in Okinawa, Japan. Trip attraction capacity and levels of the newly classified TACs was found agreeable with the amount of daily trips attracted to each center. The trip attraction data set was drawn from a 2007 Okinawa personal trip survey. This research suggests a planning methodology which guides logical transport supply routes and concentrated local development schemes.

Keywords: Effective density, urban form, auto-dependency, transport activity centers

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1514

Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

Abstract:

Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: GraphViz representation, semantic relatedness, similarity measurement, WordNet similarity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 835

Authors: Firas Salih, Luban Hameed, Afaf Kamil, Armin Bolz

Abstract:

Diagnostic and detection of the arterial stiffness is very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The photoplethysmograph signals would be processed in MATLAB. The signal will be filtered, baseline wandering removed, peaks and valleys detected and normalization of the signals should be achieved .The area under the catacrotic phase of the photoplethysmogram pulse curve is calculated using trapezoidal algorithm ; then will used in cooperation with other parameters such as age, height, blood pressure in neural network for arterial stiffness detection. The Neural network were implemented with sensitivity of 80%, accuracy 85% and specificity of 90% were got from the patients data. It is concluded that neural network can detect the arterial STIFFNESS depending on risk factor parameters.

Keywords: Arterial stiffness, area under the catacrotic phase of the photoplethysmograph pulse, neural network

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1651

Authors: Mohammad S. Laghari, Qurban A. Memon, Gulzar A. Khuwaja

Abstract:

The paper describes a knowledge based system for analysis of microscopic wear particles. Wear particles contained in lubricating oil carry important information concerning machine condition, in particular the state of wear. Experts (Tribologists) in the field extract this information to monitor the operation of the machine and ensure safety, efficiency, quality, productivity, and economy of operation. This procedure is not always objective and it can also be expensive. The aim is to classify these particles according to their morphological attributes of size, shape, edge detail, thickness ratio, color, and texture, and by using this classification thereby predict wear failure modes in engines and other machinery. The attribute knowledge links human expertise to the devised Knowledge Based Wear Particle Analysis System (KBWPAS). The system provides an automated and systematic approach to wear particle identification which is linked directly to wear processes and modes that occur in machinery. This brings consistency in wear judgment prediction which leads to standardization and also less dependence on Tribologists.

Keywords: Computer vision, knowledge based systems, morphology, wear particles.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1743

Authors: Chulhyun Kim, Seungkyum Kim, Moon-soo Kim

Abstract:

A variety of new technology-based services have emerged with the development of Information and Communication Technologies (ICTs). Since technology-based services have technology-driven characteristics, the identification of relationships between technology-based services and ICTs would give meaningful implications. Thus, this paper proposes an approach for identifying the relationships between technology-based services and ICTs by analyzing patent documents. First, business model (BM) patents are classified into relevant service categories. Second, patent citation analysis is conducted to investigate the technological linkage and impacts between technology-based services and ICTs at macro level. Third, as a micro level analysis, patent co-classification analysis is employed to identify the technological linkage and coverage. The proposed approach could guide and help managers and designers of technology-based services to discover the opportunity of the development of new technology-based services in emerging service sectors.

Keywords: Technology-based Services, Information and Communication Technology (ICT), Business Model (BM) Patent, Patent Analysis, Technological Relationship

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1988

Authors: Mohammed Erritali

Abstract:

The growth in the volume of text data such as books and articles in libraries for centuries has imposed to establish effective mechanisms to locate them. Early techniques such as abstraction, indexing and the use of classification categories have marked the birth of a new field of research called "Information Retrieval". Information Retrieval (IR) can be defined as the task of defining models and systems whose purpose is to facilitate access to a set of documents in electronic form (corpus) to allow a user to find the relevant ones for him, that is to say, the contents which matches with the information needs of the user. This paper presents a new semantic indexing approach of a documentary corpus. The indexing process starts first by a term weighting phase to determine the importance of these terms in the documents. Then the use of a thesaurus like Wordnet allows moving to the conceptual level. Each candidate concept is evaluated by determining its level of representation of the document, that is to say, the importance of the concept in relation to other concepts of the document. Finally, the semantic index is constructed by attaching to each concept of the ontology, the documents of the corpus in which these concepts are found.

Keywords: Semantic, indexing, corpora, WordNet, ontology.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1367

Authors: Yasmin Mohd Yacob, Harsa A. Mat Sakim, Nor Ashidi Mat Isa

Abstract:

Feature selection study is gaining importance due to its contribution to save classification cost in terms of time and computation load. In search of essential features, one of the methods to search the features is via the decision tree. Decision tree act as an intermediate feature space inducer in order to choose essential features. In decision tree-based feature selection, some studies used decision tree as a feature ranker with a direct threshold measure, while others remain the decision tree but utilized pruning condition that act as a threshold mechanism to choose features. This paper proposed threshold measure using Manhattan Hierarchical Cluster distance to be utilized in feature ranking in order to choose relevant features as part of the feature selection process. The result is promising, and this method can be improved in the future by including test cases of a higher number of attributes.

Keywords: Feature ranking, decision tree, hierarchical cluster, Manhattan distance.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1967

Authors: José A. D. Machuca, Bernabé Escobar-Pérez, Pedro Garrido Vega, Darkys E. Lujan García

Abstract:

Starting with an analysis of the financial and operational indicators that can be found in the specialised literature, this study aims to contribute to improvements in the performance measurement systems used when the unit of analysis is the manufacturing plant. For this a search was done in the highest impact Journals of Production and Operations Management and Management Accounting , with the aim of determining the financial and operational indicators used to evaluate performance when Advanced Production Practices have been implemented, more specifically when the practices implemented are Total Quality Management, JIT/Lean Manufacturing and Total Productive Maintenance. This has enabled us to obtain a classification of the two types of indicators based on how much each is used. For the financial indicators we have also prepared a proposal that can be adapted to manufacturing plants- accounting features. In the near future we will propose a model that links practices implementation with financial and operational indicators and these two last with each other. We aim to will test this model empirically with the data obtained in the High Performance Manufacturing Project.

Keywords: Advanced Production Practices, Financial Indicators, Non-Financial Indicators

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1505